Mapping User Trajectories to Examine Behavior and Outcomes in Digital Health Intervention Data

Annie T. Chen*, Justin H. Chang, Skyler Hallinan, David C. Mohr

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Digital health interventions pose a tremendous opportunity to increase the possibilities of treatment delivery, and with the innovations we continue to see in technologies, they are becoming increasingly pervasive. However, there are also challenges. We present FlowVis, an application which facilitates visual exploration of participants' experiences over the course of a digital health intervention. This application is based on the concept of participant trajectories, defined as paths that an individual might traverse during an intervention, characterized by key characteristics such as outcomes, usage, and qualitative data. FlowVis supports identification of subgroups of participants by similarities in their trajectories over time. We present a case study of the use of FlowVis in three parts. First, we perform exploratory analyses of the utility of different clustering methods for exploring digital health intervention data. Second, we present a flow-based visualization examining changes in participants' outcomes over the course of the intervention. Third, we compare subgroups of participants by their app usage behaviors. Though we illustrate usage of the application to explore data from one digital health intervention, the application can be applied to analyze other intervention datasets and potentially other types of performance data. This paper contributes to extant research in the visualization of digital health intervention data by proposing a visual method to examine similarities in evolutionary patterns of participants' experiences, behaviors, and outcomes over time.

Original languageEnglish (US)
Title of host publication2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781728124230
DOIs
StatePublished - Oct 2019
Event10th IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019 - Vancouver, Canada
Duration: Oct 20 2019 → …

Publication series

Name2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019

Conference

Conference10th IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019
CountryCanada
CityVancouver
Period10/20/19 → …

Keywords

  • Sankey diagram
  • cluster analysis
  • digital health intervention
  • mental health
  • mobile apps

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Media Technology
  • Health Informatics

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